------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Data/Analy
> sis zsm2020reserving.log
  log type:  text
 opened on:  21 Aug 2020, 11:03:25

. use "Treaty Obligations and Reservations zsm2020reserving.dta", replace

. 
. 
. 
. 
. 
. ***
. * Setting Global Controls
. ***
. 
. 
. * Provisions
. global provisions demanding nonderog_prov 

. global provisions2 demanding_index nonderog_prov 

. 
. * Treaties
. global treaties physinteg group_specific 

. 
. * Domestic institutions
. global institutions com_only avg_v2juhcind treateq_sup avg_nhri_powers avg_polity2 avg_fariss_latentmean

. 
. * Economic factors
. global econ avg_ln_gdp_percap avg_ln_pop_total

. 
. * Treaty dummies
. global dummies tr_cat  tr_geno tr_ccpr  tr_ced tr_cescr

. *minus tr_crmw tr_cedaw tr_cerd tr_crc tr_crpd
. 
. 
. 
. 
. 
. ***
. * Main Regression Model
. ***
. 
. * Table 2: Treaty Reservations at the Provision Level
. 
. eststo clear

. eststo A: logit reservation_5Y $provisions, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -4728.9387  
Iteration 1:   log pseudolikelihood = -4696.9104  
Iteration 2:   log pseudolikelihood = -4696.1607  
Iteration 3:   log pseudolikelihood = -4696.1603  

Logistic regression                             Number of obs     =     73,121
                                                Wald chi2(2)      =      20.20
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -4696.1603               Pseudo R2         =     0.0069

                       (Std. Err. adjusted for 1,412 clusters in country_treaty)
--------------------------------------------------------------------------------
               |               Robust
reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     demanding |   .5599376   .1246059     4.49   0.000     .3157145    .8041608
 nonderog_prov |  -.1677798    .389122    -0.43   0.666    -.9304449    .5948852
         _cons |  -4.661056   .1091797   -42.69   0.000    -4.875045   -4.447068
--------------------------------------------------------------------------------

. eststo B: logit reservation_5Y $provisions $institutions, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3328.2405  
Iteration 1:   log pseudolikelihood = -3185.4472  
Iteration 2:   log pseudolikelihood = -3152.7741  
Iteration 3:   log pseudolikelihood = -3152.1681  
Iteration 4:   log pseudolikelihood = -3152.1676  
Iteration 5:   log pseudolikelihood = -3152.1676  

Logistic regression                             Number of obs     =     52,859
                                                Wald chi2(8)      =      74.76
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3152.1676               Pseudo R2         =     0.0529

                              (Std. Err. adjusted for 1,000 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .5615284   .1460819     3.84   0.000     .2752132    .8478436
        nonderog_prov |  -.2471471   .4641625    -0.53   0.594    -1.156889    .6625947
             com_only |   1.548795   .3451409     4.49   0.000     .8723311    2.225258
        avg_v2juhcind |   .0965488   .1067319     0.90   0.366    -.1126419    .3057395
          treateq_sup |  -.1472519   .2980142    -0.49   0.621    -.7313491    .4368453
      avg_nhri_powers |  -.1225512   .0259036    -4.73   0.000    -.1733215    -.071781
          avg_polity2 |   .0046519   .0199784     0.23   0.816     -.034505    .0438088
avg_fariss_latentmean |   .0388532   .1351462     0.29   0.774    -.2260284    .3037348
                _cons |  -4.638823   .1752576   -26.47   0.000    -4.982322   -4.295325
---------------------------------------------------------------------------------------

. eststo C: logit reservation_5Y $provisions $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2857.2754  
Iteration 2:   log pseudolikelihood = -2800.4228  
Iteration 3:   log pseudolikelihood =  -2799.449  
Iteration 4:   log pseudolikelihood = -2799.4475  
Iteration 5:   log pseudolikelihood = -2799.4475  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     144.32
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2799.4475               Pseudo R2         =     0.0973

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .525767   .1511509     3.48   0.001     .2295167    .8220173
        nonderog_prov |  -.0675477   .4820628    -0.14   0.889    -1.012373     .877278
             com_only |   1.382359    .347425     3.98   0.000     .7014188      2.0633
        avg_v2juhcind |   .0303083   .1342756     0.23   0.821     -.232867    .2934836
          treateq_sup |  -.1554897   .3009037    -0.52   0.605    -.7452501    .4342708
      avg_nhri_powers |  -.1358475   .0261231    -5.20   0.000    -.1870478   -.0846472
          avg_polity2 |  -.0290329   .0245138    -1.18   0.236    -.0770791    .0190133
avg_fariss_latentmean |   .1357121   .1347551     1.01   0.314    -.1284031    .3998272
    avg_ln_gdp_percap |   .2484638   .0957447     2.60   0.009     .0608076      .43612
     avg_ln_pop_total |   .3700131   .0766087     4.83   0.000     .2198628    .5201634
                _cons |  -12.49214   1.169556   -10.68   0.000    -14.78443   -10.19985
---------------------------------------------------------------------------------------

. eststo D: logit reservation_5Y $provisions $institutions $econ $dummies, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood =   -2829.82  
Iteration 2:   log pseudolikelihood = -2761.4712  
Iteration 3:   log pseudolikelihood = -2759.2814  
Iteration 4:   log pseudolikelihood = -2759.1872  
Iteration 5:   log pseudolikelihood = -2759.1871  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(15)     =     151.21
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2759.1871               Pseudo R2         =     0.1103

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .4344564    .120318     3.61   0.000     .1986375    .6702752
        nonderog_prov |  -.5151793   .4906754    -1.05   0.294    -1.476885    .4465268
             com_only |   1.149272   .3919073     2.93   0.003     .3811478    1.917396
        avg_v2juhcind |   .0227714   .1367059     0.17   0.868    -.2451671      .29071
          treateq_sup |  -.1856126   .3157901    -0.59   0.557    -.8045498    .4333245
      avg_nhri_powers |  -.1224764   .0285476    -4.29   0.000    -.1784287   -.0665241
          avg_polity2 |  -.0282966   .0242973    -1.16   0.244    -.0759185    .0193253
avg_fariss_latentmean |   .1467097   .1329951     1.10   0.270    -.1139558    .4073752
    avg_ln_gdp_percap |   .2968623   .0947172     3.13   0.002       .11122    .4825046
     avg_ln_pop_total |   .3856464   .0791181     4.87   0.000     .2305777    .5407151
               tr_cat |  -.3729137   .6206419    -0.60   0.548     -1.58935    .8435221
              tr_geno |   .8935903   .4370091     2.04   0.041     .0370683    1.750112
              tr_ccpr |   .6353334   .3463297     1.83   0.067    -.0434603    1.314127
               tr_ced |   -2.63554   .8984321    -2.93   0.003    -4.396434   -.8746454
             tr_cescr |  -.1613723   .4058171    -0.40   0.691    -.9567592    .6340147
                _cons |  -13.11777   1.313389    -9.99   0.000    -15.69197   -10.54358
---------------------------------------------------------------------------------------

. esttab A B C D using demanding.csv, replace unstack label b(2) se(2) nomtitles indicate("Treaty Dummies = tr_*")
> /*
> */ title("Treaty Reservations at the Provision Level") addnotes("All models report clustered standard errors by 
> country-treaty.") star(+ 0.10 * 0.05 ** .01) 
(output written to demanding.csv)

. 
. logit reservation_5Y $provisions $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2857.2754  
Iteration 2:   log pseudolikelihood = -2800.4228  
Iteration 3:   log pseudolikelihood =  -2799.449  
Iteration 4:   log pseudolikelihood = -2799.4475  
Iteration 5:   log pseudolikelihood = -2799.4475  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     144.32
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2799.4475               Pseudo R2         =     0.0973

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .525767   .1511509     3.48   0.001     .2295167    .8220173
        nonderog_prov |  -.0675477   .4820628    -0.14   0.889    -1.012373     .877278
             com_only |   1.382359    .347425     3.98   0.000     .7014188      2.0633
        avg_v2juhcind |   .0303083   .1342756     0.23   0.821     -.232867    .2934836
          treateq_sup |  -.1554897   .3009037    -0.52   0.605    -.7452501    .4342708
      avg_nhri_powers |  -.1358475   .0261231    -5.20   0.000    -.1870478   -.0846472
          avg_polity2 |  -.0290329   .0245138    -1.18   0.236    -.0770791    .0190133
avg_fariss_latentmean |   .1357121   .1347551     1.01   0.314    -.1284031    .3998272
    avg_ln_gdp_percap |   .2484638   .0957447     2.60   0.009     .0608076      .43612
     avg_ln_pop_total |   .3700131   .0766087     4.83   0.000     .2198628    .5201634
                _cons |  -12.49214   1.169556   -10.68   0.000    -14.78443   -10.19985
---------------------------------------------------------------------------------------

. margins, at(demanding=(0 1))

Predictive margins                              Number of obs     =     48,640
Model VCE    : Robust

Expression   : Pr(reservation_5Y), predict()

1._at        : demanding       =           0

2._at        : demanding       =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0093276   .0012782     7.30   0.000     .0068223    .0118329
          2  |   .0154978   .0021824     7.10   0.000     .0112205    .0197752
------------------------------------------------------------------------------

. margins, at(com_only=(0 1))

Predictive margins                              Number of obs     =     48,640
Model VCE    : Robust

Expression   : Pr(reservation_5Y), predict()

1._at        : com_only        =           0

2._at        : com_only        =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0099239   .0013923     7.13   0.000     .0071951    .0126528
          2  |    .037412   .0107483     3.48   0.001     .0163457    .0584783
------------------------------------------------------------------------------

. 
. 
. 
. 
. 
. ***
. * Supplementary Regression Models
. ***
. 
. 
. * Table A1: Treaty Reservations at the Provision Level, using Individual Components of Demanding Provisions */
. 
. eststo E: logit reservation_5Y $provisions $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2857.2754  
Iteration 2:   log pseudolikelihood = -2800.4228  
Iteration 3:   log pseudolikelihood =  -2799.449  
Iteration 4:   log pseudolikelihood = -2799.4475  
Iteration 5:   log pseudolikelihood = -2799.4475  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     144.32
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2799.4475               Pseudo R2         =     0.0973

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .525767   .1511509     3.48   0.001     .2295167    .8220173
        nonderog_prov |  -.0675477   .4820628    -0.14   0.889    -1.012373     .877278
             com_only |   1.382359    .347425     3.98   0.000     .7014188      2.0633
        avg_v2juhcind |   .0303083   .1342756     0.23   0.821     -.232867    .2934836
          treateq_sup |  -.1554897   .3009037    -0.52   0.605    -.7452501    .4342708
      avg_nhri_powers |  -.1358475   .0261231    -5.20   0.000    -.1870478   -.0846472
          avg_polity2 |  -.0290329   .0245138    -1.18   0.236    -.0770791    .0190133
avg_fariss_latentmean |   .1357121   .1347551     1.01   0.314    -.1284031    .3998272
    avg_ln_gdp_percap |   .2484638   .0957447     2.60   0.009     .0608076      .43612
     avg_ln_pop_total |   .3700131   .0766087     4.83   0.000     .2198628    .5201634
                _cons |  -12.49214   1.169556   -10.68   0.000    -14.78443   -10.19985
---------------------------------------------------------------------------------------

. eststo F: logit reservation_5Y strong nonderog_prov $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2869.7908  
Iteration 2:   log pseudolikelihood = -2817.5305  
Iteration 3:   log pseudolikelihood = -2816.6602  
Iteration 4:   log pseudolikelihood = -2816.6591  
Iteration 5:   log pseudolikelihood = -2816.6591  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     134.44
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2816.6591               Pseudo R2         =     0.0917

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
               strong |   .1293468   .1533493     0.84   0.399    -.1712123    .4299059
        nonderog_prov |   .0800625   .4852491     0.16   0.869    -.8710082    1.031133
             com_only |   1.374707   .3452211     3.98   0.000     .6980859    2.051328
        avg_v2juhcind |   .0292159   .1337824     0.22   0.827    -.2329927    .2914246
          treateq_sup |  -.1382041   .2980365    -0.46   0.643    -.7223449    .4459366
      avg_nhri_powers |  -.1357458    .026064    -5.21   0.000    -.1868304   -.0846613
          avg_polity2 |  -.0278431   .0244594    -1.14   0.255    -.0757827    .0200964
avg_fariss_latentmean |    .136883   .1350484     1.01   0.311     -.127807     .401573
    avg_ln_gdp_percap |   .2473203   .0951416     2.60   0.009     .0608463    .4337944
     avg_ln_pop_total |   .3736948   .0757087     4.94   0.000     .2253085    .5220811
                _cons |  -12.39358   1.156189   -10.72   0.000    -14.65967   -10.12749
---------------------------------------------------------------------------------------

. eststo G: logit reservation_5Y precise nonderog_prov $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2860.8835  
Iteration 2:   log pseudolikelihood = -2803.9975  
Iteration 3:   log pseudolikelihood = -2803.0441  
Iteration 4:   log pseudolikelihood = -2803.0426  
Iteration 5:   log pseudolikelihood = -2803.0426  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     137.51
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2803.0426               Pseudo R2         =     0.0961

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
              precise |   .5658489   .1945867     2.91   0.004      .184466    .9472318
        nonderog_prov |   .0507917   .4808769     0.11   0.916    -.8917097     .993293
             com_only |   1.370734   .3448908     3.97   0.000     .6947608    2.046708
        avg_v2juhcind |   .0285806   .1336626     0.21   0.831    -.2333932    .2905544
          treateq_sup |  -.1396345   .2964624    -0.47   0.638    -.7206901    .4414211
      avg_nhri_powers |  -.1351989   .0260552    -5.19   0.000    -.1862661   -.0841318
          avg_polity2 |  -.0279477   .0244474    -1.14   0.253    -.0758638    .0199684
avg_fariss_latentmean |   .1334017   .1348716     0.99   0.323    -.1309417    .3977451
    avg_ln_gdp_percap |   .2511819    .094706     2.65   0.008     .0655616    .4368022
     avg_ln_pop_total |   .3727431   .0756228     4.93   0.000     .2245252    .5209611
                _cons |  -12.76813   1.168994   -10.92   0.000    -15.05931   -10.47694
---------------------------------------------------------------------------------------

. eststo H: logit reservation_5Y dom_action nonderog_prov $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2867.9724  
Iteration 2:   log pseudolikelihood = -2814.0991  
Iteration 3:   log pseudolikelihood = -2813.1906  
Iteration 4:   log pseudolikelihood = -2813.1893  
Iteration 5:   log pseudolikelihood = -2813.1893  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     140.82
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2813.1893               Pseudo R2         =     0.0929

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
           dom_action |   .5387753   .2047919     2.63   0.009     .1373906      .94016
        nonderog_prov |   .1213936   .4844621     0.25   0.802    -.8281346    1.070922
             com_only |   1.368604   .3457171     3.96   0.000     .6910105    2.046197
        avg_v2juhcind |   .0280635    .133544     0.21   0.834    -.2336779    .2898049
          treateq_sup |  -.1309791   .2961519    -0.44   0.658    -.7114262     .449468
      avg_nhri_powers |  -.1356614   .0260918    -5.20   0.000    -.1868003   -.0845224
          avg_polity2 |  -.0272329   .0244629    -1.11   0.266    -.0751792    .0207134
avg_fariss_latentmean |   .1383211   .1352359     1.02   0.306    -.1267365    .4033787
    avg_ln_gdp_percap |   .2473964    .094634     2.61   0.009     .0619172    .4328755
     avg_ln_pop_total |   .3767229   .0753881     5.00   0.000     .2289649    .5244808
                _cons |  -12.88023   1.145729   -11.24   0.000    -15.12581   -10.63464
---------------------------------------------------------------------------------------

. eststo I: logit reservation_5Y strong precise dom_action nonderog_prov $institutions $econ, vce(cluster country_
> treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2858.0074  
Iteration 2:   log pseudolikelihood = -2799.3125  
Iteration 3:   log pseudolikelihood = -2798.3148  
Iteration 4:   log pseudolikelihood = -2798.3131  
Iteration 5:   log pseudolikelihood = -2798.3131  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(12)     =     143.38
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2798.3131               Pseudo R2         =     0.0977

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
               strong |   .0699363   .1466161     0.48   0.633     -.217426    .3572986
              precise |   .5528654   .1863171     2.97   0.003     .1876907    .9180402
           dom_action |   .5305489    .205686     2.58   0.010     .1274116    .9336861
        nonderog_prov |   .0135014     .48418     0.03   0.978    -.9354739    .9624767
             com_only |   1.374246   .3443546     3.99   0.000     .6993238    2.049169
        avg_v2juhcind |   .0285538   .1337176     0.21   0.831    -.2335278    .2906354
          treateq_sup |  -.1423248   .2984806    -0.48   0.633     -.727336    .4426863
      avg_nhri_powers |  -.1357652   .0260541    -5.21   0.000    -.1868302   -.0847001
          avg_polity2 |  -.0279854   .0244176    -1.15   0.252    -.0758431    .0198722
avg_fariss_latentmean |   .1349863   .1350796     1.00   0.318    -.1297647    .3997374
    avg_ln_gdp_percap |    .249256   .0946898     2.63   0.008     .0636673    .4348447
     avg_ln_pop_total |   .3731452   .0757963     4.92   0.000     .2245871    .5217033
                _cons |  -13.28213   1.162539   -11.43   0.000    -15.56067    -11.0036
---------------------------------------------------------------------------------------

. esttab E F G H I using demanding_indiv.csv, replace unstack label b(2) se(2) nomtitles/*
> */ title("Treaty Reservations at the Provision Level, using Individual Components of Demanding Provisions")/*
> */ addnotes("All models report clustered standard errors by country-treaty.") star(+ 0.10 * 0.05 ** .01) 
(output written to demanding_indiv.csv)

. 
. 
. 
. * Table A2: Treaty Reservations at the Provision Level, using an Index of Demanding Provisions
. 
. eststo J: logit reservation_5Y $provisions2, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -4728.9387  
Iteration 1:   log pseudolikelihood = -4702.7802  
Iteration 2:   log pseudolikelihood = -4702.3443  
Iteration 3:   log pseudolikelihood = -4702.3441  

Logistic regression                             Number of obs     =     73,121
                                                Wald chi2(2)      =      14.08
                                                Prob > chi2       =     0.0009
Log pseudolikelihood = -4702.3441               Pseudo R2         =     0.0056

                        (Std. Err. adjusted for 1,412 clusters in country_treaty)
---------------------------------------------------------------------------------
                |               Robust
 reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
demanding_index |   .3413569   .0910407     3.75   0.000     .1629204    .5197935
  nonderog_prov |  -.1438495   .3882772    -0.37   0.711    -.9048589    .6171599
          _cons |  -5.183573   .2294445   -22.59   0.000    -5.633276    -4.73387
---------------------------------------------------------------------------------

. eststo K: logit reservation_5Y $provisions2 $institutions, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3328.2405  
Iteration 1:   log pseudolikelihood = -3190.4831  
Iteration 2:   log pseudolikelihood = -3158.8621  
Iteration 3:   log pseudolikelihood = -3158.4006  
Iteration 4:   log pseudolikelihood = -3158.4003  

Logistic regression                             Number of obs     =     52,859
                                                Wald chi2(8)      =      62.32
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3158.4003               Pseudo R2         =     0.0510

                              (Std. Err. adjusted for 1,000 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
      demanding_index |   .3205493    .108661     2.95   0.003     .1075776     .533521
        nonderog_prov |  -.2110904   .4634356    -0.46   0.649    -1.119408    .6972268
             com_only |   1.544981   .3459923     4.47   0.000     .8668487    2.223113
        avg_v2juhcind |   .0969336   .1063218     0.91   0.362    -.1114532    .3053205
          treateq_sup |  -.1415752   .2978585    -0.48   0.635    -.7253672    .4422168
      avg_nhri_powers |  -.1227376   .0259012    -4.74   0.000    -.1735029   -.0719723
          avg_polity2 |   .0049681   .0199277     0.25   0.803    -.0340894    .0440256
avg_fariss_latentmean |   .0369594   .1350469     0.27   0.784    -.2277276    .3016465
                _cons |  -5.112935   .3096898   -16.51   0.000    -5.719916   -4.505954
---------------------------------------------------------------------------------------

. eststo L: logit reservation_5Y $provisions2 $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2861.3163  
Iteration 2:   log pseudolikelihood =  -2805.449  
Iteration 3:   log pseudolikelihood = -2804.5109  
Iteration 4:   log pseudolikelihood = -2804.5095  
Iteration 5:   log pseudolikelihood = -2804.5095  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     135.40
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2804.5095               Pseudo R2         =     0.0957

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
      demanding_index |   .3008279   .1106691     2.72   0.007     .0839204    .5177354
        nonderog_prov |  -.0379908   .4818063    -0.08   0.937    -.9823139    .9063323
             com_only |   1.382978   .3468915     3.99   0.000     .7030834    2.062873
        avg_v2juhcind |   .0299518   .1340391     0.22   0.823      -.23276    .2926636
          treateq_sup |  -.1501398   .2994544    -0.50   0.616    -.7370596    .4367801
      avg_nhri_powers |  -.1362725   .0261069    -5.22   0.000    -.1874411    -.085104
          avg_polity2 |  -.0285352   .0244724    -1.17   0.244    -.0765001    .0194298
avg_fariss_latentmean |   .1356493   .1349411     1.01   0.315    -.1288304    .4001289
    avg_ln_gdp_percap |   .2466091   .0953901     2.59   0.010     .0596479    .4335702
     avg_ln_pop_total |   .3707432   .0762903     4.86   0.000      .221217    .5202693
                _cons |  -12.93653   1.184027   -10.93   0.000    -15.25718   -10.61588
---------------------------------------------------------------------------------------

. eststo M: logit reservation_5Y $provisions2 $institutions $econ $dummies, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2831.9778  
Iteration 2:   log pseudolikelihood = -2764.5506  
Iteration 3:   log pseudolikelihood = -2762.4159  
Iteration 4:   log pseudolikelihood = -2762.3257  
Iteration 5:   log pseudolikelihood = -2762.3256  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(15)     =     141.23
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2762.3256               Pseudo R2         =     0.1093

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
      demanding_index |   .2346143   .0957721     2.45   0.014     .0469045    .4223241
        nonderog_prov |  -.5284689   .4903161    -1.08   0.281    -1.489471    .4325329
             com_only |   1.145081   .3909629     2.93   0.003     .3788075    1.911354
        avg_v2juhcind |   .0226503   .1364933     0.17   0.868    -.2448716    .2901721
          treateq_sup |  -.1839705   .3149721    -0.58   0.559    -.8013044    .4333634
      avg_nhri_powers |  -.1221547   .0284851    -4.29   0.000    -.1779845   -.0663249
          avg_polity2 |  -.0280113   .0242383    -1.16   0.248    -.0755176     .019495
avg_fariss_latentmean |   .1451524   .1326618     1.09   0.274      -.11486    .4051647
    avg_ln_gdp_percap |   .2964408   .0943731     3.14   0.002     .1114728    .4814087
     avg_ln_pop_total |   .3851478   .0789446     4.88   0.000     .2304193    .5398764
               tr_cat |  -.3271276   .6189902    -0.53   0.597    -1.540326    .8860709
              tr_geno |   .9068484   .4350922     2.08   0.037     .0540834    1.759613
              tr_ccpr |   .6980485   .3473678     2.01   0.044     .0172201    1.378877
               tr_ced |  -2.591232   .8988672    -2.88   0.004    -4.352979   -.8294847
             tr_cescr |  -.1927568   .4089587    -0.47   0.637    -.9943011    .6087876
                _cons |  -13.45549   1.327503   -10.14   0.000    -16.05735   -10.85363
---------------------------------------------------------------------------------------

. esttab J K L M using demanding_index.csv, replace unstack label b(2) se(2) nomtitles indicate("Treaty Dummies = 
> tr_*")/*
> */ title("Treaty Reservations at the Provision Level, using an Index of Demanding Provisions")/*
> */ addnotes("All models report clustered standard errors by country-treaty.") star(+ 0.10 * 0.05 ** .01) 
(output written to demanding_index.csv)

. 
. 
. 
. * Table A3: Treaty Reservations at the Provision Level (with controls for Other Countries’ Prior Reservations)
. 
. eststo AA: logit reservation_5Y $provisions reserv_prior, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -4728.9387  
Iteration 1:   log pseudolikelihood = -4542.6819  
Iteration 2:   log pseudolikelihood = -4476.8667  
Iteration 3:   log pseudolikelihood = -4476.4834  
Iteration 4:   log pseudolikelihood = -4476.4833  

Logistic regression                             Number of obs     =     73,121
                                                Wald chi2(3)      =     127.85
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -4476.4833               Pseudo R2         =     0.0534

                       (Std. Err. adjusted for 1,412 clusters in country_treaty)
--------------------------------------------------------------------------------
               |               Robust
reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     demanding |   .7425908    .120899     6.14   0.000     .5056332    .9795484
 nonderog_prov |  -.2936038   .3824553    -0.77   0.443    -1.043203    .4559949
  reserv_prior |   .0386518   .0044169     8.75   0.000     .0299948    .0473088
         _cons |  -5.724522   .1741835   -32.86   0.000    -6.065915   -5.383128
--------------------------------------------------------------------------------

. eststo BA: logit reservation_5Y $provisions reserv_prior $institutions, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3328.2405  
Iteration 1:   log pseudolikelihood = -3066.9247  
Iteration 2:   log pseudolikelihood = -2998.8008  
Iteration 3:   log pseudolikelihood = -2996.3247  
Iteration 4:   log pseudolikelihood = -2996.3165  
Iteration 5:   log pseudolikelihood = -2996.3165  

Logistic regression                             Number of obs     =     52,859
                                                Wald chi2(9)      =     125.06
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2996.3165               Pseudo R2         =     0.0997

                              (Std. Err. adjusted for 1,000 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .7217117   .1440013     5.01   0.000     .4394744    1.003949
        nonderog_prov |  -.3076169   .4476769    -0.69   0.492    -1.185048    .5698138
         reserv_prior |   .0450416    .007072     6.37   0.000     .0311809    .0589024
             com_only |    1.44054   .3314734     4.35   0.000     .7908637    2.090216
        avg_v2juhcind |     .14471   .1009192     1.43   0.152    -.0530879    .3425079
          treateq_sup |  -.0938432   .2899437    -0.32   0.746    -.6621223    .4744359
      avg_nhri_powers |  -.0856596    .025425    -3.37   0.001    -.1354917   -.0358275
          avg_polity2 |   .0198074   .0205761     0.96   0.336     -.020521    .0601359
avg_fariss_latentmean |  -.0301201   .1303298    -0.23   0.817    -.2855617    .2253216
                _cons |  -5.859577   .2848617   -20.57   0.000    -6.417895   -5.301258
---------------------------------------------------------------------------------------

. eststo CA: logit reservation_5Y $provisions reserv_prior $institutions $econ, vce(cluster country_treaty)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2730.1289  
Iteration 2:   log pseudolikelihood = -2632.1537  
Iteration 3:   log pseudolikelihood =  -2630.296  
Iteration 4:   log pseudolikelihood = -2630.2899  
Iteration 5:   log pseudolikelihood = -2630.2899  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(11)     =     180.02
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2630.2899               Pseudo R2         =     0.1518

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .7016357   .1520512     4.61   0.000     .4036209    .9996506
        nonderog_prov |  -.2523169   .4552258    -0.55   0.579    -1.144543    .6399093
         reserv_prior |    .049216   .0071173     6.92   0.000     .0352664    .0631656
             com_only |   1.243423   .3502331     3.55   0.000     .5569784    1.929867
        avg_v2juhcind |   .0915825   .1254408     0.73   0.465    -.1542769    .3374419
          treateq_sup |  -.1247581    .316179    -0.39   0.693    -.7444575    .4949413
      avg_nhri_powers |  -.0906303   .0248991    -3.64   0.000    -.1394316    -.041829
          avg_polity2 |  -.0138108   .0243273    -0.57   0.570    -.0614913    .0338698
avg_fariss_latentmean |   .1126044   .1374271     0.82   0.413    -.1567478    .3819566
    avg_ln_gdp_percap |   .1946315   .0868715     2.24   0.025     .0243666    .3648965
     avg_ln_pop_total |   .4333452   .0744624     5.82   0.000     .2874016    .5792888
                _cons |   -14.4704    1.25087   -11.57   0.000    -16.92205   -12.01874
---------------------------------------------------------------------------------------

. eststo DA: logit reservation_5Y $provisions reserv_prior $institutions $econ $dummies, vce(cluster country_treat
> y)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2719.6024  
Iteration 2:   log pseudolikelihood = -2617.4546  
Iteration 3:   log pseudolikelihood = -2614.5263  
Iteration 4:   log pseudolikelihood = -2614.4407  
Iteration 5:   log pseudolikelihood = -2614.4406  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(16)     =     193.73
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2614.4406               Pseudo R2         =     0.1570

                                (Std. Err. adjusted for 874 clusters in country_treaty)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .630865   .1178136     5.35   0.000     .3999546    .8617754
        nonderog_prov |  -.5287152   .4998067    -1.06   0.290    -1.508318     .450888
         reserv_prior |   .0469402   .0076805     6.11   0.000     .0318867    .0619938
             com_only |   1.136927   .3752246     3.03   0.002     .4015001    1.872354
        avg_v2juhcind |   .0746765   .1280899     0.58   0.560     -.176375    .3257281
          treateq_sup |  -.1401257   .3306154    -0.42   0.672    -.7881201    .5078686
      avg_nhri_powers |  -.0847961   .0259666    -3.27   0.001    -.1356896   -.0339026
          avg_polity2 |  -.0138972   .0242906    -0.57   0.567    -.0615059    .0337114
avg_fariss_latentmean |   .1239309   .1379206     0.90   0.369    -.1463884    .3942503
    avg_ln_gdp_percap |   .2269879   .0873132     2.60   0.009     .0558573    .3981186
     avg_ln_pop_total |   .4326302   .0766305     5.65   0.000     .2824372    .5828232
               tr_cat |  -.3421704   .6017191    -0.57   0.570    -1.521518    .8371773
              tr_geno |   .8108624   .4308239     1.88   0.060     -.033537    1.655262
              tr_ccpr |   .4102919   .3527415     1.16   0.245    -.2810688    1.101653
               tr_ced |  -1.749106   .9330774    -1.87   0.061    -3.577905    .0796918
             tr_cescr |   .0978259   .4069584     0.24   0.810    -.6997979    .8954497
                _cons |  -14.65025   1.332613   -10.99   0.000    -17.26212   -12.03838
---------------------------------------------------------------------------------------

. esttab AA BA CA DA using demanding_prior.csv, replace unstack label b(2) se(2) nomtitles indicate("Treaty Dummie
> s = tr_*")/*
> */ title("Treaty Reservations at the Provision Level (with controls for Other Countries’ Prior Reservations)")/*
> */ addnotes("All models report clustered standard errors by country-treaty.") star(+ 0.10 * 0.05 ** .01) 
(output written to demanding_prior.csv)

. 
. 
. 
. * Tables A4-A7 >> See end of .do file
. 
. 
. 
. * Table A8: Treaty Reservations at the Provision Level (SE clustered by country)
. 
. eststo N: logit reservation_5Y $provisions, vce(cluster country)

Iteration 0:   log pseudolikelihood = -4728.9387  
Iteration 1:   log pseudolikelihood = -4696.9104  
Iteration 2:   log pseudolikelihood = -4696.1607  
Iteration 3:   log pseudolikelihood = -4696.1603  

Logistic regression                             Number of obs     =     73,121
                                                Wald chi2(2)      =      29.85
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -4696.1603               Pseudo R2         =     0.0069

                                (Std. Err. adjusted for 196 clusters in country)
--------------------------------------------------------------------------------
               |               Robust
reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     demanding |   .5599376   .1032065     5.43   0.000     .3576567    .7622186
 nonderog_prov |  -.1677798   .3730426    -0.45   0.653      -.89893    .5633703
         _cons |  -4.661056   .1309088   -35.61   0.000    -4.917633    -4.40448
--------------------------------------------------------------------------------

. eststo O: logit reservation_5Y $provisions $institutions, vce(cluster cow_id)

Iteration 0:   log pseudolikelihood = -3328.2405  
Iteration 1:   log pseudolikelihood = -3185.4472  
Iteration 2:   log pseudolikelihood = -3152.7741  
Iteration 3:   log pseudolikelihood = -3152.1681  
Iteration 4:   log pseudolikelihood = -3152.1676  
Iteration 5:   log pseudolikelihood = -3152.1676  

Logistic regression                             Number of obs     =     52,859
                                                Wald chi2(8)      =      61.37
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3152.1676               Pseudo R2         =     0.0529

                                        (Std. Err. adjusted for 156 clusters in cow_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .5615284    .137174     4.09   0.000     .2926723    .8303845
        nonderog_prov |  -.2471471   .4376092    -0.56   0.572    -1.104845    .6105513
             com_only |   1.548795   .4297656     3.60   0.000     .7064697     2.39112
        avg_v2juhcind |   .0965488   .1207763     0.80   0.424    -.1401683     .333266
          treateq_sup |  -.1472519   .3736932    -0.39   0.694     -.879677    .5851732
      avg_nhri_powers |  -.1225512   .0257717    -4.76   0.000    -.1730629   -.0720396
          avg_polity2 |   .0046519   .0237671     0.20   0.845    -.0419308    .0512345
avg_fariss_latentmean |   .0388532   .1599466     0.24   0.808    -.2746364    .3523428
                _cons |  -4.638823   .2112155   -21.96   0.000    -5.052798   -4.224849
---------------------------------------------------------------------------------------

. eststo P: logit reservation_5Y $provisions $institutions $econ, vce(cluster cow_id)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2857.2754  
Iteration 2:   log pseudolikelihood = -2800.4228  
Iteration 3:   log pseudolikelihood =  -2799.449  
Iteration 4:   log pseudolikelihood = -2799.4475  
Iteration 5:   log pseudolikelihood = -2799.4475  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     217.61
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2799.4475               Pseudo R2         =     0.0973

                                        (Std. Err. adjusted for 150 clusters in cow_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .525767   .1447255     3.63   0.000     .2421102    .8094238
        nonderog_prov |  -.0675477   .4589018    -0.15   0.883    -.9669788    .8318834
             com_only |   1.382359   .3167285     4.36   0.000     .7615829    2.003136
        avg_v2juhcind |   .0303083   .1540405     0.20   0.844    -.2716055    .3322221
          treateq_sup |  -.1554897   .2890721    -0.54   0.591    -.7220605    .4110811
      avg_nhri_powers |  -.1358475     .02434    -5.58   0.000    -.1835531   -.0881419
          avg_polity2 |  -.0290329   .0286474    -1.01   0.311    -.0851808     .027115
avg_fariss_latentmean |   .1357121   .1518437     0.89   0.371     -.161896    .4333202
    avg_ln_gdp_percap |   .2484638   .1080153     2.30   0.021     .0367577    .4601699
     avg_ln_pop_total |   .3700131   .0867658     4.26   0.000     .1999553    .5400708
                _cons |  -12.49214   1.285353    -9.72   0.000    -15.01139   -9.972896
---------------------------------------------------------------------------------------

. eststo Q: logit reservation_5Y $provisions $institutions $econ $dummies, vce(cluster cow_id)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood =   -2829.82  
Iteration 2:   log pseudolikelihood = -2761.4712  
Iteration 3:   log pseudolikelihood = -2759.2814  
Iteration 4:   log pseudolikelihood = -2759.1872  
Iteration 5:   log pseudolikelihood = -2759.1871  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(15)     =     322.48
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2759.1871               Pseudo R2         =     0.1103

                                        (Std. Err. adjusted for 150 clusters in cow_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .4344564   .1127088     3.85   0.000     .2135511    .6553616
        nonderog_prov |  -.5151793   .4850016    -1.06   0.288    -1.465765    .4354064
             com_only |   1.149272   .3570826     3.22   0.001     .4494028    1.849141
        avg_v2juhcind |   .0227714   .1580183     0.14   0.885    -.2869388    .3324817
          treateq_sup |  -.1856126   .2920683    -0.64   0.525    -.7580559    .3868307
      avg_nhri_powers |  -.1224764   .0262556    -4.66   0.000    -.1739364   -.0710164
          avg_polity2 |  -.0282966   .0285082    -0.99   0.321    -.0841717    .0275784
avg_fariss_latentmean |   .1467097   .1474849     0.99   0.320    -.1423553    .4357747
    avg_ln_gdp_percap |   .2968623   .1017722     2.92   0.004     .0973924    .4963322
     avg_ln_pop_total |   .3856464   .0850835     4.53   0.000     .2188858     .552407
               tr_cat |  -.3729137   .6333437    -0.59   0.556    -1.614244    .8684171
              tr_geno |   .8935903   .4334734     2.06   0.039     .0439981    1.743182
              tr_ccpr |   .6353334   .3584026     1.77   0.076    -.0671229     1.33779
               tr_ced |   -2.63554   .9454879    -2.79   0.005    -4.488662   -.7824176
             tr_cescr |  -.1613723   .3942481    -0.41   0.682    -.9340842    .6113397
                _cons |  -13.11777   1.345542    -9.75   0.000    -15.75499   -10.48056
---------------------------------------------------------------------------------------

. esttab N O P Q using demanding_SEcountry.csv, replace unstack label b(2) se(2) nomtitles indicate("Treaty Dummie
> s = tr_*")/*
> */ title("Treaty Reservations at the Provision Level (SE clustered by country)")/*
> */ addnotes("All models report clustered standard errors by country.") star(+ 0.10 * 0.05 ** .01) 
(output written to demanding_SEcountry.csv)

. 
. 
. 
. * Table A9: Treaty Reservations at the Provision Level (SE clustered by treaty)
. 
. eststo R: logit reservation_5Y $provisions, vce(cluster treaty_id)

Iteration 0:   log pseudolikelihood = -4728.9387  
Iteration 1:   log pseudolikelihood = -4696.9104  
Iteration 2:   log pseudolikelihood = -4696.1607  
Iteration 3:   log pseudolikelihood = -4696.1603  

Logistic regression                             Number of obs     =     73,121
                                                Wald chi2(2)      =       3.46
                                                Prob > chi2       =     0.1774
Log pseudolikelihood = -4696.1603               Pseudo R2         =     0.0069

                               (Std. Err. adjusted for 10 clusters in treaty_id)
--------------------------------------------------------------------------------
               |               Robust
reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     demanding |   .5599376   .3016436     1.86   0.063    -.0312731    1.151148
 nonderog_prov |  -.1677798    .281344    -0.60   0.551    -.7192039    .3836442
         _cons |  -4.661056   .3266669   -14.27   0.000    -5.301312   -4.020801
--------------------------------------------------------------------------------

. eststo S: logit reservation_5Y $provisions $institutions, vce(cluster treaty_id)

Iteration 0:   log pseudolikelihood = -3328.2405  
Iteration 1:   log pseudolikelihood = -3185.4472  
Iteration 2:   log pseudolikelihood = -3152.7741  
Iteration 3:   log pseudolikelihood = -3152.1681  
Iteration 4:   log pseudolikelihood = -3152.1676  
Iteration 5:   log pseudolikelihood = -3152.1676  

Logistic regression                             Number of obs     =     52,859
                                                Wald chi2(8)      =    2867.65
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3152.1676               Pseudo R2         =     0.0529

                                      (Std. Err. adjusted for 10 clusters in treaty_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .5615284   .2666315     2.11   0.035     .0389403    1.084117
        nonderog_prov |  -.2471471   .1879931    -1.31   0.189    -.6156067    .1213126
             com_only |   1.548795    .500385     3.10   0.002     .5680581    2.529531
        avg_v2juhcind |   .0965488   .0896343     1.08   0.281    -.0791312    .2722289
          treateq_sup |  -.1472519   .2168728    -0.68   0.497    -.5723148     .277811
      avg_nhri_powers |  -.1225512   .0241983    -5.06   0.000     -.169979   -.0751234
          avg_polity2 |   .0046519   .0341966     0.14   0.892    -.0623721    .0716759
avg_fariss_latentmean |   .0388532   .0926756     0.42   0.675    -.1427875     .220494
                _cons |  -4.638823   .2976822   -15.58   0.000     -5.22227   -4.055377
---------------------------------------------------------------------------------------

. eststo T: logit reservation_5Y $provisions $institutions $econ, vce(cluster treaty_id)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood = -2857.2754  
Iteration 2:   log pseudolikelihood = -2800.4228  
Iteration 3:   log pseudolikelihood =  -2799.449  
Iteration 4:   log pseudolikelihood = -2799.4475  
Iteration 5:   log pseudolikelihood = -2799.4475  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(8)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -2799.4475               Pseudo R2         =     0.0973

                                      (Std. Err. adjusted for 10 clusters in treaty_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .525767   .3053337     1.72   0.085    -.0726761     1.12421
        nonderog_prov |  -.0675477   .2092148    -0.32   0.747    -.4776011    .3425057
             com_only |   1.382359   .5866342     2.36   0.018     .2325773    2.532141
        avg_v2juhcind |   .0303083   .1130711     0.27   0.789    -.1913071    .2519237
          treateq_sup |  -.1554897   .2213299    -0.70   0.482    -.5892883    .2783089
      avg_nhri_powers |  -.1358475   .0245778    -5.53   0.000     -.184019    -.087676
          avg_polity2 |  -.0290329   .0364641    -0.80   0.426    -.1005012    .0424355
avg_fariss_latentmean |   .1357121   .1106173     1.23   0.220    -.0810938    .3525179
    avg_ln_gdp_percap |   .2484638   .1081369     2.30   0.022     .0365194    .4604082
     avg_ln_pop_total |   .3700131   .0501374     7.38   0.000     .2717456    .4682805
                _cons |  -12.49214   1.187631   -10.52   0.000    -14.81986   -10.16443
---------------------------------------------------------------------------------------

. eststo U: logit reservation_5Y $provisions $institutions $econ $dummies, vce(cluster treaty_id)

Iteration 0:   log pseudolikelihood = -3101.1892  
Iteration 1:   log pseudolikelihood =   -2829.82  
Iteration 2:   log pseudolikelihood = -2761.4712  
Iteration 3:   log pseudolikelihood = -2759.2814  
Iteration 4:   log pseudolikelihood = -2759.1872  
Iteration 5:   log pseudolikelihood = -2759.1871  

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(9)      =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -2759.1871               Pseudo R2         =     0.1103

                                      (Std. Err. adjusted for 10 clusters in treaty_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .4344564   .2558212     1.70   0.089     -.066944    .9358567
        nonderog_prov |  -.5151793   .0401969   -12.82   0.000    -.5939638   -.4363948
             com_only |   1.149272   .6436755     1.79   0.074    -.1123088    2.410853
        avg_v2juhcind |   .0227714   .1129714     0.20   0.840    -.1986484    .2441912
          treateq_sup |  -.1856126   .2311768    -0.80   0.422    -.6387108    .2674855
      avg_nhri_powers |  -.1224764   .0296712    -4.13   0.000    -.1806308    -.064322
          avg_polity2 |  -.0282966   .0347943    -0.81   0.416    -.0964922     .039899
avg_fariss_latentmean |   .1467097   .0964983     1.52   0.128    -.0424235    .3358428
    avg_ln_gdp_percap |   .2968623   .0870177     3.41   0.001     .1263107     .467414
     avg_ln_pop_total |   .3856464   .0516617     7.46   0.000     .2843913    .4869016
               tr_cat |  -.3729137   .4404061    -0.85   0.397    -1.236094    .4902663
              tr_geno |   .8935903   .4475897     2.00   0.046     .0163305     1.77085
              tr_ccpr |   .6353334   .4285119     1.48   0.138    -.2045344    1.475201
               tr_ced |   -2.63554   .5547536    -4.75   0.000    -3.722837   -1.548243
             tr_cescr |  -.1613723   .4645347    -0.35   0.728    -1.071843    .7490989
                _cons |  -13.11777   1.402096    -9.36   0.000    -15.86583   -10.36972
---------------------------------------------------------------------------------------

. esttab R S T U using demanding_SEtreaty.csv, replace unstack label b(2) se(2) nomtitles indicate("Treaty Dummies
>  = tr_*")/*
> */ title("Treaty Reservations at the Provision Level (SE clustered by treaty")/*
> */ addnotes("All models report clustered standard errors by treaty.") star(+ 0.10 * 0.05 ** .01) 
(output written to demanding_SEtreaty.csv)

. 
. 
. 
. * Table A10: Treaty Reservations at the Provision Level (multiway clustering)
. 
. eststo V: vcemway logit reservation_5Y $provisions, cluster(cow_id country_treaty treaty_id provision_id)

Logistic regression                             Number of obs     =     73,118
                                                Wald chi2(2)      =      29.71
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -4683.2489               Pseudo R2         =     0.0069

(Std. Err. adjusted for clustering on cow_id country_treaty treaty_id provision_id)
--------------------------------------------------------------------------------
               |               Robust
reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     demanding |   .5576061   .2965492     1.88   0.060    -.0236197    1.138832
 nonderog_prov |  -.1633571   .2578913    -0.63   0.526    -.6688148    .3421006
         _cons |  -4.663483   .3337688   -13.97   0.000    -5.317658   -4.009308
--------------------------------------------------------------------------------
Notes:
    Std. Err. adjusted for 4-way clustering on cow_id country_treaty treaty_id provision_id
      Number of clusters in cow_id       = 198
      Number of clusters in country_tr~y = 1411
      Number of clusters in treaty_id    = 10
      Number of clusters in provision_id = 572

    Stata's default small-cluster correction factors have been applied. See vcemway for detail.

    chi2() and Prob > chi2 above only account for one-way clustering on cow_id.
      Use test to compute chi2() and Prob > chi2 that account for 4-way clustering.

. eststo W: vcemway logit reservation_5Y $provisions $institutions, cluster(cow_id country_treaty treaty_id provis
> ion_id)

Logistic regression                             Number of obs     =     52,859
                                                Wald chi2(8)      =      61.37
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3152.1676               Pseudo R2         =     0.0529

    (Std. Err. adjusted for clustering on cow_id country_treaty treaty_id provision_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .5615284   .2630497     2.13   0.033     .0459606    1.077096
        nonderog_prov |  -.2471471   .1667238    -1.48   0.138    -.5739197    .0796255
             com_only |   1.548795   .5624587     2.75   0.006      .446396    2.651194
        avg_v2juhcind |   .0965488   .1070702     0.90   0.367     -.113305    .3064026
          treateq_sup |  -.1472519   .3153148    -0.47   0.641    -.7652575    .4707537
      avg_nhri_powers |  -.1225512   .0267299    -4.58   0.000    -.1749408   -.0701616
          avg_polity2 |   .0046519   .0372169     0.12   0.901    -.0682919    .0775957
avg_fariss_latentmean |   .0388532    .130975     0.30   0.767    -.2178531    .2955595
                _cons |  -4.638823   .3216698   -14.42   0.000    -5.269285   -4.008362
---------------------------------------------------------------------------------------
Notes:
    Std. Err. adjusted for 4-way clustering on cow_id country_treaty treaty_id provision_id
      Number of clusters in cow_id       = 156
      Number of clusters in country_tr~y = 1000
      Number of clusters in treaty_id    = 10
      Number of clusters in provision_id = 572

    Stata's default small-cluster correction factors have been applied. See vcemway for detail.

    chi2() and Prob > chi2 above only account for one-way clustering on cow_id.
      Use test to compute chi2() and Prob > chi2 that account for 4-way clustering.

. eststo X: vcemway logit reservation_5Y $provisions $institutions $econ, cluster(cow_id country_treaty treaty_id 
> provision_id)

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(10)     =     217.61
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2799.4475               Pseudo R2         =     0.0973

    (Std. Err. adjusted for clustering on cow_id country_treaty treaty_id provision_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |    .525767   .3067401     1.71   0.087    -.0754325    1.126966
        nonderog_prov |  -.0675477   .2069026    -0.33   0.744    -.4730694     .337974
             com_only |   1.382359    .572113     2.42   0.016     .2610384     2.50368
        avg_v2juhcind |   .0303083   .1395297     0.22   0.828    -.2431649    .3037815
          treateq_sup |  -.1554897   .2235458    -0.70   0.487    -.5936314     .282652
      avg_nhri_powers |  -.1358475   .0261816    -5.19   0.000    -.1871624   -.0845326
          avg_polity2 |  -.0290329   .0470321    -0.62   0.537    -.1212141    .0631483
avg_fariss_latentmean |   .1357121   .1338285     1.01   0.311     -.126587    .3980111
    avg_ln_gdp_percap |   .2484638   .1203039     2.07   0.039     .0126726     .484255
     avg_ln_pop_total |   .3700131   .0651459     5.68   0.000     .2423294    .4976967
                _cons |  -12.49214   1.301812    -9.60   0.000    -15.04365   -9.940637
---------------------------------------------------------------------------------------
Notes:
    Std. Err. adjusted for 4-way clustering on cow_id country_treaty treaty_id provision_id
      Number of clusters in cow_id       = 150
      Number of clusters in country_tr~y = 874
      Number of clusters in treaty_id    = 10
      Number of clusters in provision_id = 572

    Stata's default small-cluster correction factors have been applied. See vcemway for detail.

    chi2() and Prob > chi2 above only account for one-way clustering on cow_id.
      Use test to compute chi2() and Prob > chi2 that account for 4-way clustering.

. eststo Y: vcemway logit reservation_5Y $provisions $institutions $econ $dummies, cluster(cow_id country_treaty t
> reaty_id provision_id)

Logistic regression                             Number of obs     =     48,640
                                                Wald chi2(15)     =     322.48
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2759.1871               Pseudo R2         =     0.1103

    (Std. Err. adjusted for clustering on cow_id country_treaty treaty_id provision_id)
---------------------------------------------------------------------------------------
                      |               Robust
       reservation_5Y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            demanding |   .4344564   .2588307     1.68   0.093    -.0728425    .9417553
        nonderog_prov |  -.5151793   .3029022    -1.70   0.089    -1.108857    .0784981
             com_only |   1.149272   .6261494     1.84   0.066    -.0779583    2.376502
        avg_v2juhcind |   .0227714   .1387313     0.16   0.870     -.249137    .2946798
          treateq_sup |  -.1856126   .2564012    -0.72   0.469    -.6881498    .3169245
      avg_nhri_powers |  -.1224764   .0304443    -4.02   0.000    -.1821462   -.0628067
          avg_polity2 |  -.0282966   .0488907    -0.58   0.563    -.1241207    .0675274
avg_fariss_latentmean |   .1467097   .1340693     1.09   0.274    -.1160614    .4094808
    avg_ln_gdp_percap |   .2968623   .1048404     2.83   0.005      .091379    .5023457
     avg_ln_pop_total |   .3856464   .0628915     6.13   0.000     .2623814    .5089115
               tr_cat |  -.3729137   .5413881    -0.69   0.491    -1.434015    .6881875
              tr_geno |   .8935903    .451631     1.98   0.048     .0084099    1.778771
              tr_ccpr |   .6353334   .4575075     1.39   0.165    -.2613648    1.532032
               tr_ced |   -2.63554   .6377986    -4.13   0.000    -3.885602   -1.385478
             tr_cescr |  -.1613723   .4739734    -0.34   0.734    -1.090343    .7675984
                _cons |  -13.11777   1.433088    -9.15   0.000    -15.92658   -10.30897
---------------------------------------------------------------------------------------
Notes:
    Std. Err. adjusted for 4-way clustering on cow_id country_treaty treaty_id provision_id
      Number of clusters in cow_id       = 150
      Number of clusters in country_tr~y = 874
      Number of clusters in treaty_id    = 10
      Number of clusters in provision_id = 572

    Stata's default small-cluster correction factors have been applied. See vcemway for detail.

    chi2() and Prob > chi2 above only account for one-way clustering on cow_id.
      Use test to compute chi2() and Prob > chi2 that account for 4-way clustering.

. esttab V W X Y using demanding_SEmultiway.csv,  replace unstack label b(2) se(2) nomtitles indicate("Treaty Dumm
> ies = tr_*")/*
> */title("Treaty Reservations at the Provision Level (multiway clustering)")/*
> */ addnotes("All models report clustered standard errors by country, country-treaty, treaty, and provision.") st
> ar(+ 0.10 * 0.05 ** .01) 
(output written to demanding_SEmultiway.csv)

. 
. 
. 
. 
. 
. ***
. * Coefficient plots
. ***
. 
. 
. * Figure 7: Predicted Effect of Variables on the Likelihood of Reservation, with 95 percent CIs
. 
. eststo plot1: sem (reservation_5Y <- $provisions $institutions $econ, vce(cluster country_treaty))
(24481 observations with missing values excluded)

Endogenous variables

Observed:  reservation_5Y

Exogenous variables

Observed:  demanding nonderog_prov com_only avg_v2juhcind treateq_sup avg_nhri_powers avg_polity2
           avg_fariss_latentmean avg_ln_gdp_percap avg_ln_pop_total

Fitting target model:

Iteration 0:   log pseudolikelihood = -608145.64  
Iteration 1:   log pseudolikelihood = -608145.64  

Structural equation model                       Number of obs     =     48,640
Estimation method  = ml
Log pseudolikelihood= -608145.64

                                  (Std. Err. adjusted for 874 clusters in country_treaty)
-----------------------------------------------------------------------------------------
                        |               Robust
                        |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
Structural              |
  reservation_5Y <-     |
              demanding |   .0064668   .0020456     3.16   0.002     .0024575     .010476
          nonderog_prov |   .0005291   .0067376     0.08   0.937    -.0126762    .0137345
               com_only |    .034488   .0105188     3.28   0.001     .0138715    .0551045
          avg_v2juhcind |   .0001542   .0013231     0.12   0.907    -.0024389    .0027474
            treateq_sup |   .0009044   .0030409     0.30   0.766    -.0050556    .0068645
        avg_nhri_powers |  -.0014533   .0002746    -5.29   0.000    -.0019915   -.0009151
            avg_polity2 |   -.000258   .0002333    -1.11   0.269    -.0007153    .0001994
  avg_fariss_latentmean |   .0026519   .0015517     1.71   0.087    -.0003894    .0056932
      avg_ln_gdp_percap |   .0028907   .0011033     2.62   0.009     .0007283    .0050531
       avg_ln_pop_total |   .0056033   .0013027     4.30   0.000     .0030501    .0081565
                  _cons |  -.1000939   .0207119    -4.83   0.000    -.1406886   -.0594992
------------------------+----------------------------------------------------------------
   var(e.reservation_5Y)|   .0113986   .0013607                      .0090206    .0144034
-----------------------------------------------------------------------------------------

. coefplot, drop(_cons) xline(0) xlabel(, nogrid) ylabel(, nogrid) b(b_std) v(V_std) xtitle(Standardized Coefficie
> nts)  level(95) 

. graph export "/Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures
> /Figure 7.eps", replace
(file /Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures/Figure 7.
> eps written in EPS format)

. 
. 
. 
. * Figure A2: Predicted Effect of Variables on the Likelihood of Reservation, with 95 percent CIs
. * (Individual Components of Demanding Provisions)
. 
. eststo plot2: sem (reservation_5Y <- strong precise dom_action nonderog_prov $institutions $econ, vce(cluster co
> untry_treaty))
(24481 observations with missing values excluded)

Endogenous variables

Observed:  reservation_5Y

Exogenous variables

Observed:  strong precise dom_action nonderog_prov com_only avg_v2juhcind treateq_sup avg_nhri_powers
           avg_polity2 avg_fariss_latentmean avg_ln_gdp_percap avg_ln_pop_total

Fitting target model:

Iteration 0:   log pseudolikelihood =  -644949.4  
Iteration 1:   log pseudolikelihood =  -644949.4  

Structural equation model                       Number of obs     =     48,640
Estimation method  = ml
Log pseudolikelihood=  -644949.4

                                  (Std. Err. adjusted for 874 clusters in country_treaty)
-----------------------------------------------------------------------------------------
                        |               Robust
                        |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
Structural              |
  reservation_5Y <-     |
                 strong |   .0011382    .001674     0.68   0.497    -.0021428    .0044192
                precise |   .0056145    .001668     3.37   0.001     .0023454    .0088837
             dom_action |   .0046763   .0015668     2.98   0.003     .0016054    .0077471
          nonderog_prov |   .0015646   .0067495     0.23   0.817    -.0116642    .0147935
               com_only |   .0343478   .0105048     3.27   0.001     .0137587    .0549369
          avg_v2juhcind |   .0001396   .0013203     0.11   0.916    -.0024482    .0027273
            treateq_sup |   .0010159   .0030411     0.33   0.738    -.0049446    .0069764
        avg_nhri_powers |  -.0014475   .0002744    -5.28   0.000    -.0019853   -.0009097
            avg_polity2 |  -.0002484   .0002325    -1.07   0.285    -.0007041    .0002073
  avg_fariss_latentmean |   .0026336   .0015536     1.70   0.090    -.0004114    .0056787
      avg_ln_gdp_percap |   .0028923   .0011004     2.63   0.009     .0007355    .0050491
       avg_ln_pop_total |   .0056315   .0013043     4.32   0.000     .0030752    .0081878
                  _cons |  -.1070813   .0212965    -5.03   0.000    -.1488217   -.0653409
------------------------+----------------------------------------------------------------
   var(e.reservation_5Y)|   .0113995   .0013615                      .0090202    .0144063
-----------------------------------------------------------------------------------------

. coefplot, drop(_cons) xline(0) xlabel(, nogrid) ylabel(, nogrid) b(b_std) v(V_std) xtitle(Standardized Coefficie
> nts)  level(95) 

. graph export "/Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures
> /Figure A2.eps", replace
(file /Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures/Figure A2
> .eps written in EPS format)

. 
. 
. 
. * Figure A3: Predicted Effect of Variables on the Likelihood of Reservation, with 95 percent CIs
. * (Dichotomous Measure vs. Index of Demandingness)
. 
. eststo Main: sem (reservation_5Y <- $institutions $econ nonderog_prov demanding, vce(cluster country_treaty))
(24481 observations with missing values excluded)

Endogenous variables

Observed:  reservation_5Y

Exogenous variables

Observed:  com_only avg_v2juhcind treateq_sup avg_nhri_powers avg_polity2 avg_fariss_latentmean
           avg_ln_gdp_percap avg_ln_pop_total nonderog_prov demanding

Fitting target model:

Iteration 0:   log pseudolikelihood = -608145.64  
Iteration 1:   log pseudolikelihood = -608145.64  

Structural equation model                       Number of obs     =     48,640
Estimation method  = ml
Log pseudolikelihood= -608145.64

                                  (Std. Err. adjusted for 874 clusters in country_treaty)
-----------------------------------------------------------------------------------------
                        |               Robust
                        |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
Structural              |
  reservation_5Y <-     |
               com_only |    .034488   .0105188     3.28   0.001     .0138715    .0551045
          avg_v2juhcind |   .0001542   .0013231     0.12   0.907    -.0024389    .0027474
            treateq_sup |   .0009044   .0030409     0.30   0.766    -.0050556    .0068645
        avg_nhri_powers |  -.0014533   .0002746    -5.29   0.000    -.0019915   -.0009151
            avg_polity2 |   -.000258   .0002333    -1.11   0.269    -.0007153    .0001994
  avg_fariss_latentmean |   .0026519   .0015517     1.71   0.087    -.0003894    .0056932
      avg_ln_gdp_percap |   .0028907   .0011033     2.62   0.009     .0007283    .0050531
       avg_ln_pop_total |   .0056033   .0013027     4.30   0.000     .0030501    .0081565
          nonderog_prov |   .0005291   .0067376     0.08   0.937    -.0126762    .0137345
              demanding |   .0064668   .0020456     3.16   0.002     .0024575     .010476
                  _cons |  -.1000939   .0207119    -4.83   0.000    -.1406886   -.0594992
------------------------+----------------------------------------------------------------
   var(e.reservation_5Y)|   .0113986   .0013607                      .0090206    .0144034
-----------------------------------------------------------------------------------------

. eststo Supplementary: sem (reservation_5Y <- $institutions $econ nonderog_prov demanding_index, vce(cluster coun
> try_treaty))
(24481 observations with missing values excluded)

Endogenous variables

Observed:  reservation_5Y

Exogenous variables

Observed:  com_only avg_v2juhcind treateq_sup avg_nhri_powers avg_polity2 avg_fariss_latentmean
           avg_ln_gdp_percap avg_ln_pop_total nonderog_prov demanding_index

Fitting target model:

Iteration 0:   log pseudolikelihood = -630247.03  
Iteration 1:   log pseudolikelihood = -630247.03  

Structural equation model                       Number of obs     =     48,640
Estimation method  = ml
Log pseudolikelihood= -630247.03

                                  (Std. Err. adjusted for 874 clusters in country_treaty)
-----------------------------------------------------------------------------------------
                        |               Robust
                        |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
Structural              |
  reservation_5Y <-     |
               com_only |   .0344771   .0105326     3.27   0.001     .0138335    .0551207
          avg_v2juhcind |   .0001523   .0013224     0.12   0.908    -.0024395    .0027441
            treateq_sup |   .0009619   .0030386     0.32   0.752    -.0049936    .0069175
        avg_nhri_powers |  -.0014559   .0002752    -5.29   0.000    -.0019954   -.0009165
            avg_polity2 |  -.0002539    .000233    -1.09   0.276    -.0007105    .0002028
  avg_fariss_latentmean |   .0026421   .0015533     1.70   0.089    -.0004022    .0056865
      avg_ln_gdp_percap |   .0028721   .0011028     2.60   0.009     .0007107    .0050336
       avg_ln_pop_total |   .0056145    .001304     4.31   0.000     .0030587    .0081703
          nonderog_prov |   .0010069   .0067322     0.15   0.881    -.0121879    .0142017
        demanding_index |   .0034157    .001206     2.83   0.005      .001052    .0057795
                  _cons |  -.1050986   .0212785    -4.94   0.000    -.1468037   -.0633935
------------------------+----------------------------------------------------------------
   var(e.reservation_5Y)|   .0114016   .0013618                      .0090219    .0144089
-----------------------------------------------------------------------------------------

. coefplot Main Supplementary, drop(_cons) xline(0) xlabel(, nogrid) ylabel(, nogrid) b(b_std) v(V_std) xtitle(Sta
> ndardized Coefficients) level(95)

. graph export "/Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures
> /Figure A3.eps", replace
(file /Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures/Figure A3
> .eps written in EPS format)

. 
. 
. 
. 
. 
. ***
. * Difference in means
. ***
. 
. 
. clear

. import excel "/Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Data/di
> ff_of_means zsm2020reserving.xlsx", sheet("Sheet1") firstrow

. 
. 
. * Figure A1: Average Reservations by Obligation Type
. 
. graph bar (asis) Yes No, over(dimension, sort(order)) bar(1, color(gs0*3)) bar(2, color(gs0*.5)) /*
> */ytitle("Average Number of Reservations", size(small))/*
> */note("Obligation Type",  size(small) pos(6) nobexpand)  graphregion(margin(zero)) /*
> */caption("All differences are statistically significant at p<0.001",  size(vsmall) pos(7))  graphregion(margin(
> zero))

. graph export "/Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures
> /Figure A1.eps", replace
(file /Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Figures/Figure A1
> .eps written in EPS format)

. 
. 
. 
. 
. 
. ***
. * Crosstabs
. ***
. 
. 
. clear

. use "/Users/kelebogilezvobgo/Dropbox/Human Rights Treaty Reservations/_ISQ submission/ISQ_FINAL/Data/Treaty Obli
> gations zsm2020reserving.dta", replace

. 
. 
. * Table A4: Demanding Provisions
. 
. tab demanding

    Strong, |
 precise, & |
   requires |
   domestic |
     action |      Freq.     Percent        Cum.
------------+-----------------------------------
      0. no |        519       59.52       59.52
     1. yes |        353       40.48      100.00
------------+-----------------------------------
      Total |        872      100.00

. 
. 
. * Table A5: Strength and Domestic Action
. 
. tab strong dom_action

           |      dom_action
    strong | 0. no dom  1. domest |     Total
-----------+----------------------+----------
   0. weak |        32        380 |       412 
 1. strong |        44        416 |       460 
-----------+----------------------+----------
     Total |        76        796 |       872 


. 
. 
. * Table A6: Precision and Domestic Action
. 
. tab precise dom_action

             |      dom_action
     precise | 0. no dom  1. domest |     Total
-------------+----------------------+----------
0. imprecise |        22        183 |       205 
  1. precise |        54        613 |       667 
-------------+----------------------+----------
       Total |        76        796 |       872 


. 
. 
. * Table A7: Strength and Precision
. 
. tab strong precise

           |        precise
    strong | 0. imprec  1. precis |     Total
-----------+----------------------+----------
   0. weak |       128        284 |       412 
 1. strong |        77        383 |       460 
-----------+----------------------+----------
     Total |       205        667 |       872 


. 
end of do-file

